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Abstract Details
Activity Number:
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108
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Type:
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Invited
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Date/Time:
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Monday, July 30, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Teaching of Statistics in the Health Sciences
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Abstract - #303721 |
Title:
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Teaching and Learning Confounding in the Health Sciences
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Author(s):
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Felicity Enders*+ and Miranda Kroehl*+ and Rickey Carter*+ and John McGready*+
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Companies:
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Mayo Clinic and University of Colorado at Denver and Mayo Clinic and The Johns Hopkins University
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Address:
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200 First Street, SW, Rochester, MN, 55905, 4309 W. 35th Ave, Denver, CO, 80212, 200 First Street, SW, Rochester, MN, 55905, 615 N. Wolfe Street, RM E3543, Baltimore, MD, 21205-2179,
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Keywords:
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statistics education ;
confounding ;
problem-based learning
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Abstract:
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In order to read or publish in the medical research literature, students in the health sciences need a thorough understanding of confounding. However, research shows that confounding may be poorly understood by some students even after two courses in biostatistics at the graduate level. We introduce two problem-based guided examples to increase both the breadth and depth of students' understanding of this challenging subject. The first is a visual introduction to confounding and interaction in which students naturally lead the discussion through a set of increasingly complex models. The second example links the analysis to study design and compares results for a t test, a t test performed within the context of regression, and an adjusted analysis termed an "adjusted t test" to help link understanding. We also identify topics for improved teaching for such a challenging subject as confounding, with the goal of removing barriers to student understanding.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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